We investigate the learnt user embeddings in more detail. In particular, we plot random samples of users on a 2D-plane using t-SNE [1]}. The users who have greater sarcastic comments (atleast 2 more than the other type) are termed as sarcastic users (colored red). Conversely, the users having lesser sarcastic comments are called non-sarcastic users (colored green). Equal number of users from both the categories are plotted. We aim to analyze the reason behind the performance boost provided by the user embeddings as shown in Table REF . We see in Figure REF  that both the user types belong to similar distributions. However, the sarcastic users have a greater spread than the non-sarcastic ones (red belt around the green region). This is also evident from the variances of the distributions where the sarcastic distribution comprises of \(10.92\)  variance as opposed to \(5.20\)  variance of the non-sarcastic distribution. We can infer from this observation that the user embeddings belonging to this non-overlapping red-region provide discriminative information regarding the sarcastic tendencies of their users.
